Method and system for providing high efficiency, bidirectional messaging for low latency applications

ABSTRACT

A system and a method for routing a message to an application over a connection oriented session in a Kafka messaging platform environment are provided. The method includes: acquiring a plurality of partitions from the Kafka messaging platform; designating a first partition from among the plurality of partitions as a sticky partition; generating a plurality of routing keys that are configured to route to the sticky partition; receiving a subscription from a service that corresponds to a first application; transmitting, to the first application, a first routing key that identifies the subscription from among the plurality of routing keys; and receiving messages from Kafka services that are routed by the first routing key to the first application. For any particular application or set of applications, a plurality of connection oriented sessions may be used to achieve load balancing and high availability.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional PatentApplication Ser. No. 63/036,752, filed Jun. 9, 2020, which is herebyincorporated by reference in its entirety.

This application is being filed concurrently on Nov. 4, 2020 with eachof U.S. patent application Ser. No. 17/089,275, entitled “Method andSystem for Interaction Servicing”; U.S. patent application Ser. No.17/089,305, entitled “Method and System for Interaction Servicing withEmbeddable Ribbon Display”; U.S. patent application Ser. No. 17/089,302,entitled “Method and System for Resolving Producer and ConsumerAffinities in Interaction Servicing”; U.S. patent application Ser. No.17/089,311, entitled “Method and System for Providing Resiliency inInteraction Servicing”; U.S. patent application Ser. No. 17/089,061,entitled “Method and System for Providing Resiliency in InteractionServicing Across Data Centers”; U.S. patent application Ser. No.17/089,093, entitled “Method and System for Providing Resiliency inInteraction Servicing Across Data Centers”; and U.S. patent applicationSer. No. 17/089,145, entitled “Method and System for Providing HighEfficiency, Bidirectional Messaging for Low Latency Applications,” thecontents of each of which is hereby incorporated by reference in itsrespective entirety.

BACKGROUND 1. Field of the Disclosure

This technology generally relates to methods and systems for performingcustomer service interactions, and more particularly to methods andsystems for integrating and streamlining large number of customerservice interactions to ensure efficient and accurate interactionservicing results.

2. Background Information

For a large corporate organization that has many customers, customerservice is an important aspect of the business operation. Customerstypically expect service requests to be handled in a timely and accuratemanner, and if the corporate organization fails to provide such customerservice, there may be a negative effect on the reputation of thatorganization.

Many customer service requests are performed online via the Internet.For such requests, it is important that the request be assessed androuted to the correct entity within the corporate organization, togetherwith all of the relevant information that will be needed by the entitythat will handle the request. However, the proper routing and handlingof such requests may be complicated when the number of requests is largeand the size of the corporate organization is large.

Accordingly, there is a need for a tool that integrates and streamlinesthe processing of customer service interactions in order to ensureefficient and accurate handling and resolution thereof.

SUMMARY

The present disclosure, through one or more of its various aspects,embodiments, and/or specific features or sub-components, provides, interalia, various systems, servers, devices, methods, media, programs, andplatforms for handling large number of customer service interactions toensure efficient and accurate interaction servicing results.

According to an aspect of the present disclosure, a method for servicinga plurality of interactions with users is provided. The method isimplemented by at least one processor. The method includes: receiving,by the at least one processor from each respective user, a respectiverequest for a corresponding interaction; obtaining, by the at least oneprocessor for each interaction, request-specific information thatrelates to the received respective request and user-specific informationthat relates to the respective user; analyzing, by the at least oneprocessor for each interaction, the request-specific information todetermine at least one corresponding microservice that is usable forhandling the interaction; and routing, by the at least one processor foreach interaction, the request-specific information and the user-specificinformation to a respective destination that relates to the determinedat least one corresponding microservice.

The method may further include receiving, by the at least one processorfrom the at least one corresponding microservice, response informationthat relates to a response to the respective request for thecorresponding interaction.

The method may further include displaying, by the at least processor forat least one interaction, a screen that includes at least a subset ofthe request-specific information, at least a subset of the user-specificinformation, and status information that relates to a status of theresponse to the respective request for the at least one interaction.

The method may further include determining, for each interaction, arequest type for each respective request, the request type including atleast one from among a voice request, an email request, an online chatrequest, a browser request, and a click-to-call request.

The analyzing may further include analyzing the request-specificinformation to determine at least two corresponding microservices thatare usable for handling the corresponding interaction.

The method may further include determining at least two separate routeshaving at least two different destinations that correspond to thedetermined at least two corresponding microservices; and using at leastone metric that relates to a workload distribution to select an optimumroute from among the determined at least two separate routes. Therouting may further include using the selected optimum route.

According to another exemplary embodiment, a method for routing amessage to an application in a Kafka messaging platform environment isprovided. The method is implemented by at least one processor. Themethod includes: acquiring, by the at least one processor, a pluralityof partitions from the Kafka messaging platform; designating, by the atleast one processor, a first partition from among the plurality ofpartitions as a sticky partition; generating, by the at least oneprocessor, a plurality of routing keys that are configured to route tothe sticky partition; using, by the at least one processor, a firstrouting key from among the plurality of routing keys for a first servicesubscription; processing, by the at least one processor, a firstapplication subscription from a first connection oriented session from afirst application, and returning the first routing key as a firstsubscription identifier; removing by the at least one processor, thefirst routing key from plurality of routing keys for a subsequent clientsubscription; and receiving, by the at least one processor, a messagetransmitted by a second service using the first subscription identifieras a routing key.

The method may further include: using a custom Kafka sticky partitionassignor to acquire a first plurality of metadata that relates to asticky partition priority; and determining, for each of the firstplurality of metadata, a respective highest priority partition for whicha corresponding assignment does not change.

The generating of the plurality of routing keys may include generating aplurality of random keys; applying a Kafka hash-plus-modulo algorithm tothe random keys; and retaining the keys that map to the stickypartition.

The generating of the plurality of routing keys may include generating aplurality of random keys; producing the random keys to an inbound topic;and when the keys are consumed, storing keys that are from the stickypartition.

The method may further include: associating, by the at least oneprocessor, a first data center identification with a Kafka messagingplatform cluster identification and a topic identification; caching, bythe at least one processor, the first data center identification withthe first subscription identifier; determining the first data centeridentification when an event is received; and routing the event by usingthe first subscription identifier and the first data centeridentification to select a target Kafka cluster based on the associatedKafka messaging platform cluster identification and the associated topicidentification.

The method may further include: receiving, by the at least oneprocessor, a first event from among a plurality of event, with a timeduration for which the first event is valid; determining that the timeduration for which the first event is valid has been exceeded; anddropping the first event.

According to yet another exemplary embodiment, a method forload-balancing a delivery of messages over a plurality of connectionoriented sessions from a plurality of applications is provided. Themethod is implemented by at least one processor in a Kafka messagingplatform environment. The method includes: obtaining, by the at leastone processor, a first subscription from a first application containinga first load balancing group identification; assigning, by the at leastone processor, a first subscription identification to the firstsubscription; caching, by the at least one processor, a mapping of thefirst load balancing group identification to a list of subscriptionidentifications and a mapping of the first subscription identificationto a connection oriented session; transmitting, to the first applicationby the at least one processor, a subscribe response that includes thefirst subscription identification; receiving, by the at least oneprocessor, a notification event that includes the first subscriptionidentification; and attempting, by the at least one processor, todeliver a message to the first application when the cached firstsubscription identification maps to a connection oriented session of thefirst application.

The notification event may be received from an event provider that hasreceived the notification event and randomly selected the firstsubscription identification from the list of subscriptionidentifications.

The method may further include: when the attempting to deliver themessage fails when using a first connection oriented session thatcorresponds to the first subscription identification, using the list ofsubscription identifications to identify a second connection orientedsession that relates to a second application for which a correspondingsubscription identification has a matching load balancing groupidentification as the first connection oriented session; and attemptingto deliver the message to the second application.

The method may further include: evaluating, by the at least oneprocessor, a total number of subscription identifications for a firstavailability zone from among a plurality of availability zones and forthe first load balancing group identification from among a plurality ofload balancing group identifications; and triggering, by the at leastone processor, a redistribution of connection oriented sessions with thefirst application.

According to still another exemplary embodiment, a method for ensuring adelivery of a message in a Kafka messaging platform environment despitea network connection failure is provided. The method is implemented byat least one processor. The method includes: obtaining, by the at leastone processor from a first application, a first subscription containinga first high availability group identification; assigning, by the atleast one processor, a first subscription identification to the firstsubscription; caching, by the at least one processor, a mapping of thefirst high availability group identification to an ordered list ofsubscription identifications; transmitting, to the first application bythe at least one processor, a subscribe response that includes the firstsubscription identification; receiving, by the at least one processor, anotification event that includes the first subscription identification;and attempting, by the at least one processor, to deliver a message tothe first application when the first subscription identification matchesa connection oriented session subscription of the first application.

The notification event may be received from an event provider thatselected the first subscription identification from the ordered list ofsubscription identifications based on the first subscriptionidentification being listed first in an order of the ordered list.

The method may further include: when the attempting to deliver themessage fails, determining, from the ordered list of subscriptionidentifications, at least one subscription identification for which ahigh availability group identification matches the first highavailability group identification of the first subscription, andidentifying a second subscription identification that matches a secondconnection oriented session of the first application; and attempting todeliver the message to the first application using the second connectionoriented session.

BRIEF DESCRIPTION OF THE DRAWINGS

The present disclosure is further described in the detailed descriptionwhich follows, in reference to the noted plurality of drawings, by wayof non-limiting examples of preferred embodiments of the presentdisclosure, in which like characters represent like elements throughoutthe several views of the drawings.

FIG. 1 illustrates an exemplary computer system.

FIG. 2 illustrates an exemplary diagram of a network environment.

FIG. 3 shows an exemplary system for implementing a method for handlinglarge number of customer service interactions to ensure efficient andaccurate interaction servicing results.

FIG. 4 is a flowchart of an exemplary process for implementing a methodfor handling large number of customer service interactions to ensureefficient and accurate interaction servicing results.

FIG. 5 is a first screenshot that illustrates a user interface forhandling a customer interaction, according to an exemplary embodiment.

FIG. 6 is a second screenshot that illustrates customer identificationinformation that is displayable on the user interface for handling acustomer interaction, according to an exemplary embodiment.

FIG. 7 is a diagram that illustrates a plurality of microservices andcorresponding routing paths for implementing a method for handling largenumber of customer service interactions to ensure efficient and accurateinteraction servicing results, according to an exemplary embodiment.

FIG. 8 is a data flow diagram that illustrates consumer affinity in an amessaging platform environment, according to an exemplary embodiment.

FIG. 9 is a flowchart of a method for routing a message to anapplication in a messaging platform environment, according to anexemplary embodiment.

FIG. 10 is a flowchart of a method for load-balancing a delivery ofmessages in a messaging platform environment, according to an exemplaryembodiment.

FIG. 11 is a flowchart of a method for ensuring a delivery of a messagein a messaging platform environment despite a network connectionfailure, according to an exemplary embodiment.

DETAILED DESCRIPTION

Through one or more of its various aspects, embodiments and/or specificfeatures or sub-components of the present disclosure, are intended tobring out one or more of the advantages as specifically described aboveand noted below.

The examples may also be embodied as one or more non-transitory computerreadable media having instructions stored thereon for one or moreaspects of the present technology as described and illustrated by way ofthe examples herein. The instructions in some examples includeexecutable code that, when executed by one or more processors, cause theprocessors to carry out steps necessary to implement the methods of theexamples of this technology that are described and illustrated herein.

FIG. 1 is an exemplary system for use in accordance with the embodimentsdescribed herein. The system 100 is generally shown and may include acomputer system 102, which is generally indicated.

The computer system 102 may include a set of instructions that can beexecuted to cause the computer system 102 to perform any one or more ofthe methods or computer-based functions disclosed herein, either aloneor in combination with the other described devices. The computer system102 may operate as a standalone device or may be connected to othersystems or peripheral devices. For example, the computer system 102 mayinclude, or be included within, any one or more computers, servers,systems, communication networks or cloud environment. Even further, theinstructions may be operative in such cloud-based computing environment.

In a networked deployment, the computer system 102 may operate in thecapacity of a server or as a client user computer in a server-clientuser network environment, a client user computer in a cloud computingenvironment, or as a peer computer system in a peer-to-peer (ordistributed) network environment. The computer system 102, or portionsthereof, may be implemented as, or incorporated into, various devices,such as a personal computer, a tablet computer, a set-top box, apersonal digital assistant, a mobile device, a palmtop computer, alaptop computer, a desktop computer, a communications device, a wirelesssmart phone, a personal trusted device, a wearable device, a globalpositioning satellite (GPS) device, a web appliance, a device that isrunning the Apple iOS operating system, a device that is running theAndroid operating system, a device that is capable of running a webbrowser to connect to the Internet, or any other machine capable ofexecuting a set of instructions (sequential or otherwise) that specifyactions to be taken by that machine. Further, while a single computersystem 102 is illustrated, additional embodiments may include anycollection of systems or sub-systems that individually or jointlyexecute instructions or perform functions. The term “system” shall betaken throughout the present disclosure to include any collection ofsystems or sub-systems that individually or jointly execute a set, ormultiple sets, of instructions to perform one or more computerfunctions.

As illustrated in FIG. 1, the computer system 102 may include at leastone processor 104. The processor 104 is tangible and non-transitory. Asused herein, the term “non-transitory” is to be interpreted not as aneternal characteristic of a state, but as a characteristic of a statethat will last for a period of time. The term “non-transitory”specifically disavows fleeting characteristics such as characteristicsof a particular carrier wave or signal or other forms that exist onlytransitorily in any place at any time. The processor 104 is an articleof manufacture and/or a machine component. The processor 104 isconfigured to execute software instructions in order to performfunctions as described in the various embodiments herein. The processor104 may be a general-purpose processor or may be part of an applicationspecific integrated circuit (ASIC). The processor 104 may also be amicroprocessor, a microcomputer, a processor chip, a controller, amicrocontroller, a digital signal processor (DSP), a state machine, or aprogrammable logic device. The processor 104 may also be a logicalcircuit, including a programmable gate array (PGA) such as a fieldprogrammable gate array (FPGA), or another type of circuit that includesdiscrete gate and/or transistor logic. The processor 104 may be acentral processing unit (CPU), a graphics processing unit (GPU), orboth. Additionally, any processor described herein may include multipleprocessors, parallel processors, or both. Multiple processors may beincluded in, or coupled to, a single device or multiple devices.

The computer system 102 may also include a computer memory 106. Thecomputer memory 106 may include a static memory, a dynamic memory, orboth in communication. Memories described herein are tangible storagemediums that can store data as well as executable instructions and arenon-transitory during the time instructions are stored therein. Again,as used herein, the term “non-transitory” is to be interpreted not as aneternal characteristic of a state, but as a characteristic of a statethat will last for a period of time. The term “non-transitory”specifically disavows fleeting characteristics such as characteristicsof a particular carrier wave or signal or other forms that exist onlytransitorily in any place at any time. The memories are an article ofmanufacture and/or machine component. Memories described herein arecomputer-readable mediums from which data and executable instructionscan be read by a computer. Memories as described herein may be randomaccess memory (RAM), read only memory (ROM), flash memory, electricallyprogrammable read only memory (EPROM), electrically erasableprogrammable read-only memory (EEPROM), registers, a hard disk, a cache,a removable disk, tape, compact disk read only memory (CD-ROM), digitalversatile disk (DVD), floppy disk, blu-ray disk, or any other form ofstorage medium known in the art. Memories may be volatile ornon-volatile, secure and/or encrypted, unsecure and/or unencrypted. Ofcourse, the computer memory 106 may comprise any combination of memoriesor a single storage.

The computer system 102 may further include a display 108, such as aliquid crystal display (LCD), an organic light emitting diode (OLED), aflat panel display, a solid state display, a cathode ray tube (CRT), aplasma display, or any other type of display, examples of which are wellknown to skilled persons.

The computer system 102 may also include at least one input device 110,such as a keyboard, a touch-sensitive input screen or pad, a speechinput, a mouse, a remote control device having a wireless keypad, amicrophone coupled to a speech recognition engine, a camera such as avideo camera or still camera, a cursor control device, a globalpositioning system (GPS) device, an altimeter, a gyroscope, anaccelerometer, a proximity sensor, or any combination thereof. Thoseskilled in the art appreciate that various embodiments of the computersystem 102 may include multiple input devices 110. Moreover, thoseskilled in the art further appreciate that the above-listed, exemplaryinput devices 110 are not meant to be exhaustive and that the computersystem 102 may include any additional, or alternative, input devices110.

The computer system 102 may also include a medium reader 112 which isconfigured to read any one or more sets of instructions, e.g. software,from any of the memories described herein. The instructions, whenexecuted by a processor, can be used to perform one or more of themethods and processes as described herein. In a particular embodiment,the instructions may reside completely, or at least partially, withinthe memory 106, the medium reader 112, and/or the processor 110 duringexecution by the computer system 102.

Furthermore, the computer system 102 may include any additional devices,components, parts, peripherals, hardware, software or any combinationthereof which are commonly known and understood as being included withor within a computer system, such as, but not limited to, a networkinterface 114 and an output device 116. The output device 116 may be,but is not limited to, a speaker, an audio out, a video out, aremote-control output, a printer, or any combination thereof.

Each of the components of the computer system 102 may be interconnectedand communicate via a bus 118 or other communication link. Asillustrated in FIG. 1, the components may each be interconnected andcommunicate via an internal bus. However, those skilled in the artappreciate that any of the components may also be connected via anexpansion bus. Moreover, the bus 118 may enable communication via anystandard or other specification commonly known and understood such as,but not limited to, peripheral component interconnect, peripheralcomponent interconnect express, parallel advanced technology attachment,serial advanced technology attachment, etc.

The computer system 102 may be in communication with one or moreadditional computer devices 120 via a network 122. The network 122 maybe, but is not limited to, a local area network, a wide area network,the Internet, a telephony network, a short-range network, or any othernetwork commonly known and understood in the art. The short-rangenetwork may include, for example, Bluetooth, Zigbee, infrared, nearfield communication, ultraband, or any combination thereof. Thoseskilled in the art appreciate that additional networks 122 which areknown and understood may additionally or alternatively be used and thatthe exemplary networks 122 are not limiting or exhaustive. Also, whilethe network 122 is illustrated in FIG. 1 as a wireless network, thoseskilled in the art appreciate that the network 122 may also be a wirednetwork.

The additional computer device 120 is illustrated in FIG. 1 as apersonal computer. However, those skilled in the art appreciate that, inalternative embodiments of the present application, the computer device120 may be a laptop computer, a tablet PC, a personal digital assistant,a mobile device, a palmtop computer, a desktop computer, acommunications device, a wireless telephone, a personal trusted device,a web appliance, a server, a device that is running the Apple iOSoperating system, a device that is running the Android operating system,a device that is capable of running a web browser to connect to theInternet, or any other device that is capable of executing a set ofinstructions, sequential or otherwise, that specify actions to be takenby that device. Of course, those skilled in the art appreciate that theabove-listed devices are merely exemplary devices and that the device120 may be any additional device or apparatus commonly known andunderstood in the art without departing from the scope of the presentapplication. For example, the computer device 120 may be the same orsimilar to the computer system 102. Furthermore, those skilled in theart similarly understand that the device may be any combination ofdevices and apparatuses.

Of course, those skilled in the art appreciate that the above-listedcomponents of the computer system 102 are merely meant to be exemplaryand are not intended to be exhaustive and/or inclusive. Furthermore, theexamples of the components listed above are also meant to be exemplaryand similarly are not meant to be exhaustive and/or inclusive.

In accordance with various embodiments of the present disclosure, themethods described herein may be implemented using a hardware computersystem that executes software programs. Further, in an exemplary,non-limited embodiment, implementations can include distributedprocessing, component/object distributed processing, and parallelprocessing. Virtual computer system processing can be constructed toimplement one or more of the methods or functionalities as describedherein, and a processor described herein may be used to support avirtual processing environment.

As described herein, various embodiments provide optimized methods andsystems for handling large number of customer service interactions toensure efficient and accurate interaction servicing results.

Referring to FIG. 2, a schematic of an exemplary network environment 200for implementing a method for handling large number of customer serviceinteractions to ensure efficient and accurate interaction servicingresults is illustrated. In an exemplary embodiment, the method isexecutable on any networked computer platform, such as, for example, apersonal computer (PC), a device that is running the Apple iOS operatingsystem, a device that is running the Android operating system, or adevice that is capable of running a web browser to connect to theInternet.

The method for handling large number of customer service interactions toensure efficient and accurate interaction servicing results may beimplemented by an Interaction Servicing Fabric (ISF) device 202. The ISFdevice 202 may be the same or similar to the computer system 102 asdescribed with respect to FIG. 1. The ISF device 202 may store one ormore applications that can include executable instructions that, whenexecuted by the ISF device 202, cause the ISF device 202 to performactions, such as to transmit, receive, or otherwise process networkmessages, for example, and to perform other actions described andillustrated below with reference to the figures. The application(s) maybe implemented as modules or components of other applications. Further,the application(s) can be implemented as operating system extensions,modules, plugins, or the like.

Even further, the application(s) may be operative in a cloud-basedcomputing environment. The application(s) may be executed within or asvirtual machine(s) or virtual server(s) that may be managed in acloud-based computing environment. Also, the application(s), and eventhe ISF device 202 itself, may be located in virtual server(s) runningin a cloud-based computing environment rather than being tied to one ormore specific physical network computing devices. Also, theapplication(s) may be running in one or more virtual machines (VMs)executing on the ISF device 202. Additionally, in one or moreembodiments of this technology, virtual machine(s) running on the ISFdevice 202 may be managed or supervised by a hypervisor.

In the network environment 200 of FIG. 2, the ISF device 202 is coupledto a plurality of server devices 204(1)-204(n) that hosts a plurality ofdatabases 206(1)-206(n), and also to a plurality of client devices208(1)-208(n) via communication network(s) 210. A communicationinterface of the ISF device 202, such as the network interface 114 ofthe computer system 102 of FIG. 1, operatively couples and communicatesbetween the ISF device 202, the server devices 204(1)-204(n), and/or theclient devices 208(1)-208(n), which are all coupled together by thecommunication network(s) 210, although other types and/or numbers ofcommunication networks or systems with other types and/or numbers ofconnections and/or configurations to other devices and/or elements mayalso be used.

The communication network(s) 210 may be the same or similar to thenetwork 122 as described with respect to FIG. 1, although the ISF device202, the server devices 204(1)-204(n), and/or the client devices208(1)-208(n) may be coupled together via other topologies.Additionally, the network environment 200 may include other networkdevices such as one or more routers and/or switches, for example, whichare well known in the art and thus will not be described herein. Thistechnology provides a number of advantages including methods,non-transitory computer readable media, and ISF devices that efficientlyimplement methods and systems for handling large number of customerservice interactions to ensure efficient and accurate interactionservicing results.

By way of example only, the communication network(s) 210 may includelocal area network(s) (LAN(s)) or wide area network(s) (WAN(s)), and canuse TCP/IP over Ethernet and industry-standard protocols, although othertypes and/or numbers of protocols and/or communication networks may beused. The communication network(s) 210 in this example may employ anysuitable interface mechanisms and network communication technologiesincluding, for example, teletraffic in any suitable form (e.g., voice,modem, and the like), Public Switched Telephone Network (PSTNs),Ethernet-based Packet Data Networks (PDNs), combinations thereof, andthe like.

The ISF device 202 may be a standalone device or integrated with one ormore other devices or apparatuses, such as one or more of the serverdevices 204(1)-204(n), for example. In one particular example, the ISFdevice 202 may include or be hosted by one of the server devices204(1)-204(n), and other arrangements are also possible. Moreover, oneor more of the devices of the ISF device 202 may be in a same or adifferent communication network including one or more public, private,or cloud networks, for example.

The plurality of server devices 204(1)-204(n) may be the same or similarto the computer system 102 or the computer device 120 as described withrespect to FIG. 1, including any features or combination of featuresdescribed with respect thereto. For example, any of the server devices204(1)-204(n) may include, among other features, one or more processors,a memory, and a communication interface, which are coupled together by abus or other communication link, although other numbers and/or types ofnetwork devices may be used. The server devices 204(1)-204(n) in thisexample may process requests received from the ISF device 202 via thecommunication network(s) 210 according to the HTTP-based and/orJavaScript Object Notation (JSON) protocol, for example, although otherprotocols may also be used.

The server devices 204(1)-204(n) may be hardware or software or mayrepresent a system with multiple servers in a pool, which may includeinternal or external networks. An Availability Zone is equivalent to apool. The server devices 204(1)-204(n) hosts the databases 206(1)-206(n)that are configured to store data that relates to user requests,identification information that relates to individual users, andmicroservices that are used for resolving user requests.

Although the server devices 204(1)-204(n) are illustrated as singledevices, one or more actions of each of the server devices 204(1)-204(n)may be distributed across one or more distinct network computing devicesthat together comprise one or more of the server devices 204(1)-204(n).Moreover, the server devices 204(1)-204(n) are not limited to aparticular configuration. Thus, the server devices 204(1)-204(n) maycontain a plurality of network computing devices that operate using amaster/slave approach, whereby one of the network computing devices ofthe server devices 204(1)-204(n) operates to manage and/or otherwisecoordinate operations of the other network computing devices.

The server devices 204(1)-204(n) may operate as a plurality of networkcomputing devices within a cluster architecture, a peer-to peerarchitecture, virtual machines, or within a cloud architecture, forexample. Thus, the technology disclosed herein is not to be construed asbeing limited to a single environment and other configurations andarchitectures are also envisaged.

The plurality of client devices 208(1)-208(n) may also be the same orsimilar to the computer system 102 or the computer device 120 asdescribed with respect to FIG. 1, including any features or combinationof features described with respect thereto. For example, the clientdevices 208(1)-208(n) in this example may include any type of computingdevice that can interact with the ISF device 202 via communicationnetwork(s) 210. Accordingly, the client devices 208(1)-208(n) may bemobile computing devices, desktop computing devices, laptop computingdevices, tablet computing devices, virtual machines (includingcloud-based computers), or the like, that host chat, e-mail, orvoice-to-text applications, for example. In an exemplary embodiment, atleast one client device 208 is a wireless mobile communication device,i.e., a smart phone.

The client devices 208(1)-208(n) may run interface applications, such asstandard web browsers or standalone client applications, which mayprovide an interface to communicate with the ISF device 202 via thecommunication network(s) 210 in order to communicate user requests andinformation. The client devices 208(1)-208(n) may further include, amongother features, a display device, such as a display screen ortouchscreen, and/or an input device, such as a keyboard, for example.

Although the exemplary network environment 200 with the ISF device 202,the server devices 204(1)-204(n), the client devices 208(1)-208(n), andthe communication network(s) 210 are described and illustrated herein,other types and/or numbers of systems, devices, components, and/orelements in other topologies may be used. It is to be understood thatthe systems of the examples described herein are for exemplary purposes,as many variations of the specific hardware and software used toimplement the examples are possible, as will be appreciated by thoseskilled in the relevant art(s).

One or more of the devices depicted in the network environment 200, suchas the ISF device 202, the server devices 204(1)-204(n), or the clientdevices 208(1)-208(n), for example, may be configured to operate asvirtual instances on the same physical machine. In other words, one ormore of the ISF device 202, the server devices 204(1)-204(n), or theclient devices 208(1)-208(n) may operate on the same physical devicerather than as separate devices communicating through communicationnetwork(s) 210. Additionally, there may be more or fewer ISF devices202, server devices 204(1)-204(n), or client devices 208(1)-208(n) thanillustrated in FIG. 2.

In addition, two or more computing systems or devices may be substitutedfor any one of the systems or devices in any example. Accordingly,principles and advantages of distributed processing, such as redundancyand replication also may be implemented, as desired, to increase therobustness and performance of the devices and systems of the examples.The examples may also be implemented on computer system(s) that extendacross any suitable network using any suitable interface mechanisms andtraffic technologies, including by way of example only teletraffic inany suitable form (e.g., voice and modem), wireless traffic networks,cellular traffic networks, Packet Data Networks (PDNs), the Internet,intranets, and combinations thereof.

The ISF device 202 is described and illustrated in FIG. 3 as includingan interaction services routing and handling module 302, although it mayinclude other rules, policies, modules, databases, or applications, forexample. As will be described below, the interaction services routingand handling module 302 is configured to implement a method for handlinglarge number of customer service interactions to ensure efficient andaccurate interaction servicing results.

An exemplary process 300 for implementing a mechanism for handling largenumber of customer service interactions to ensure efficient and accurateinteraction servicing results by utilizing the network environment ofFIG. 2 is illustrated as being executed in FIG. 3. Specifically, a firstclient device 208(1) and a second client device 208(2) are illustratedas being in communication with ISF device 202. In this regard, the firstclient device 208(1) and the second client device 208(2) may be“clients” of the ISF device 202 and are described herein as such.Nevertheless, it is to be known and understood that the first clientdevice 208(1) and/or the second client device 208(2) need notnecessarily be “clients” of the ISF device 202, or any entity describedin association therewith herein.

Any additional or alternative relationship may exist between either orboth of the first client device 208(1) and the second client device208(2) and the ISF device 202, or no relationship may exist. Forexample, the ISF device 202 and the first client device 208(1) may beconfigured as the same physical device.

Further, ISF device 202 is illustrated as being able to access amicroservices data repository 206(1) and a user-specific identificationinformation database 206(2). The interaction services routing andhandling module 302 may be configured to access these databases forimplementing a method for handling large number of customer serviceinteractions to ensure efficient and accurate interaction servicingresults.

The first client device 208(1) may be, for example, a smart phone. Ofcourse, the first client device 208(1) may be any additional devicedescribed herein. The second client device 208(2) may be, for example, apersonal computer (PC). Of course, the second client device 208(2) mayalso be any additional device described herein.

The process may be executed via the communication network(s) 210, whichmay comprise plural networks as described above. For example, in anexemplary embodiment, either or both of the first client device 208(1)and the second client device 208(2) may communicate with the ISF device202 via broadband or cellular communication. Alternatively, the processmay be executed by the ISF device 202 in a standalone manner, e.g., by asmart phone on which the interaction services routing and handlingmodule 302 has been downloaded. Of course, these embodiments are merelyexemplary and are not limiting or exhaustive.

Upon being started, a processor that is hosted in the ISF device 202executes a process for handling large number of customer serviceinteractions to ensure efficient and accurate interaction servicingresults. An exemplary process for handling large number of customerservice interactions to ensure efficient and accurate interactionservicing results is generally indicated at flowchart 400 in FIG. 4.

In process 400 of FIG. 4, at step S402, the interaction services routingand handling module 302 receives, from each of a plurality of users, arespective request for a corresponding interaction. At step S404, theinteraction services routing and handling module 302 obtainsrequest-specific information that relates to each respective request anduser-specific information that relates to each respective user. In anexemplary embodiment, the interaction services routing and handlingmodule 302 prompts each user to enter the user-specific information viaa graphical user interface that is displayed on the screen of a clientdevice 208.

Further, the interaction services routing and handling module 302 mayalso display, on a screen of the IDF device 202, a user interface forhandling an interaction request that includes at least a subset of therequest-specific information and at least a subset of the user-specificinformation. For example, referring to FIG. 5, a first screenshot 500that illustrates a user interface for handling a customer interactionmay include a task bar at the top of the screen, a trapezoidal-shapedribbon that includes request-specific information and user-specificinformation at the top right-hand portion of the screen, a menu and alist of recent interactions along the left side of the screen, andstatus information relating to the current interaction request in thebody of the screen. As another example, referring to FIG. 6, a secondscreenshot 600 that illustrates the user interface may include moredetails of the user-specific information, together with thetrapezoidal-shaped ribbon shown in FIG. 5.

At step S406, the interaction services routing and handling module 302determines, for each interaction, a request type for each respectiverequest. The request type may indicate a communication mode by which aparticular request is received. In an exemplary embodiment, the requesttype may include at least one of a voice request, an email request, anonline chat request, a browser request, and a click-to-call request.

At step S408, the interaction services routing and handling module 302analyzes, for each requested interaction, the request-specificinformation in order to determine at least one correspondingmicroservice and/or at least one microservice instance that is usablefor handling the interaction. In an exemplary embodiment, theinteraction services routing and handling module may determine more thanone such microservice. For example, there may be any number ofmicroservices that are suitable for handling different aspects of aninteraction, such as two (2), three (3), five (5), ten (10), twenty(20), fifty (50), one hundred (100), or more such microservices; andsome of these may have overlapping functions. As another example, theremay be multiple microservice instances, which refers to using oneparticular microservice multiple times.

At step S410, the interaction services routing and handling module 302determines at least one suitable route for transmitting therequest-specific information and the user-specific information for eachrespective interaction to a respective destination that relates to themicroservices determined in step S408. In an exemplary embodiment, forany given interaction, there may be more than one suitable route andmore than one suitable destination, depending on the microservices to beused, and also depending on the order of using the microservices. As aresult, the interaction services routing and handling module 302 maydetermine two or more suitable routes and/or two or more suitabledestinations for a particular interaction. Then, at step S412, theinteraction services routing and handling module 302 uses a metric thatrelates to workload distribution for selecting an optimum route; and atstep S414, the interaction services routing and handling module 302 usesthe optimum route for routing the information.

FIG. 7 is a diagram 700 that illustrates a plurality of microservicesand corresponding routing paths for implementing a method for handlinglarge number of customer service interactions to ensure efficient andaccurate interaction servicing results, according to an exemplaryembodiment. As illustrated in FIG. 7, a large number of microservicesmay be available for handling a particular request with respect to aninteraction, including microservices having the following descriptors:“resource state”; “attribution”; “event listener”; “auditor”; “warmchannel transfer”; “qualification”; “resource assign”; “eventprocessor”; “monitor”; “flow processor”; “channel adapters”; “rulesprocessor”; “get customer journey”; “specialist login”; “get specialistprofile”; “get contacts”; “get communication history”; “receive voice &video call”; “invoke automated chat”; “invoke social”; “auditor”;“invoke simple chat”; “invoke conversation (multimedia)”; setdisposition”; and “get customer journey”.

Further, as also illustrated in FIG. 7 and in accordance with anexemplary embodiment, the microservices may be depicted in ahoneycomb-type hexagonal pattern. In this manner, the analyzing of aparticular interaction effectively breaks up the associated tasks intorelatively small pieces that correspond to different microservices. Inan exemplary embodiment, a cloud native microservices-basedimplementation, such as Kafka, is used, and in this construct, thehoneycombs communicate with one other via events. The use of such animplementation provides several advantages, including the following: 1)Events must arrive in the proper order and must be scalable. 2) Bypartitioning the interactions, there is a low latency with respect toincreasing or decreasing the number of microservices to be used (furthernoting that lower processing latency may be achieved by increasing thenumber of microservice instances). 3) By virtue of the ordering and thescalability of events, the interaction services handling module 302achieves a higher throughput, thereby speeding up processing. 4) Loadbalancing and caching of IP addresses also contributes to higherprocessing speeds. 5) The ability to identify multiple redundancies inconnections between microservices provides system resiliency androbustness. In an exemplary embodiment, events relating to a specificuser session must be consumed in exactly the same order as the eventswere produced. Events relating to multiple user sessions need not beconsumed, relative to each other, in the order in which they wereproduced. Distinguishing between events relating to a specific usersession and events relating to multiple user sessions in this manner mayfacilitate a greater parallel processing capacity.

At step S416, the interaction services routing and handling module 302receives response information that relates to a respective response foreach corresponding request. In this aspect, in many situations, thereceived response effectively concludes the interaction.

In an exemplary embodiment, a cloud native microservice approach for anomni-channel contact center is provided. This approach includesdecomposed contract bases microservices and a microservices-basedevent-driven architecture that resides in the cloud and is designed tohave an elastic scale, high availability, and high resiliency, with aservice level agreement (SLA) that is higher than 99.999%. The contactcenter is a real time (millisecond, sub-second latency) architecturethat has an extensive intrinsic design. Groups of microservices arecreated in order to provide different aspects of functionality. Thestack includes a platform as a service (i.e., microservices platform,such as, for example, Kubernetes or Cloud Foundry), Kafka scalable eventmessaging and streaming technology, Cassandra, NoSQL performant privatedatabase for microservices, and distributed in-memory grid technologiessuch as, for example, Cloud Cache, for storing quickly accessible stateinformation.

The general architecture includes a facade layer of microservicesadapting to external vendor elements through predetermined protocols,and normalizing the communication to fit a highly available, concurrentprocessing, resilient, large-scale, event-based communication; KafkaTopics for ordered events to consuming instances of microservices;client-facing microservices which consume raw Kafka events from facademicroservices and provide discrete functional services with aclient-facing application programming interface (API)—RESTful WebServices; a general purpose notification service that provides abidirectional low latency event exchange mechanism between clients(e.g., single user web clients) or server applications (e.g., fraudecosystems, voice biometric systems, analytics, and/or recordingsystems); web clients following microservices architecture with userinterface (UI), software development kit (SDK), and Servicesarchitecture using Angular8 frameworks; drop-in concept for specialistphone control applications into various servicing applicationsdelivering a computer telephony integration (CTI) container with all ofthe functionality included therein; programmatic APIs for screen pop;and standalone ribbon. Clusters of microservices are provided for coreservicing fabric telephony and agent login; automated specialistprovisioning across multiple vendor solutions for orchestration,routing, recording, voicemail, and other functionalities; specialistphone control; and real-time dashboard for contact center supervisorypersonnel.

In another exemplary embodiment, a client ribbon embedding mechanismthat is suitable for a large scale deployment and integration with keyvalue pairs (KVPs) for screen pops is provided. The client ribbonembedding mechanism includes a self-contained feature set that isextensible to omni-channel without requiring extensive deployment andknowledge of CTI protocols and APIs by non-contact center developers.The mechanism creates a lightweight approach to integrating contactcenter specialist features into the servicing application, therebyproviding a quicker rollout, reduced integration effort, and automaticupdates for easier maintenance. The mechanism includes standardizedintegration patterns and a cookbook recipe approach, and provides a wayto obtain integrated features required by servicing applications. Thesefeatures may include: screen pops; updating customer relevant data; endcall tracking; state change tied to case disposition; transfer andconference events; customized call notifications; and enabling key valueobservers (KVOs) to be updated by servicing applications, middleware,and fraud authentication systems.

In yet another exemplary embodiment, a Kafka usage for convertingstateful ordered events to stateless, scalable eventing in real time isprovided. The design includes concurrent data-center (DC) andpool-specific active and backup topics on multiple Kafka clusters inorder to handle catastrophic pool failures. In an exemplary embodiment,a pool refers to an instance of the cloud platform so that multiplepools within a DC provide resiliency in the event of a failure of asingle pool (e.g., a bad network router). Other features includecross-DC Kafka events to provide a telephony service that is abstractedfrom an affinity to one of many DC's. The use of a Kafka routing keythat is tied to directory numbers (DNs) and design in partitioning mayalso be provided, in order to cause ordered events to go to particularconsumers in a scalable manner. A sticky Kafka partition assignor toreduce latencies when the cloud system automatically scales up or downmay also be provided, for overcoming a need to rebalance and/or resendon multiple hops that may otherwise introduce latencies. A sequentialthread executor may also be provided to distinguish between events thatmay be processed in parallel from those that must be processedsequentially.

The Kafka usage may include a sticky pool-aware Kafka partition assignorto enable a cloud system to automatically scale up or down despite poolaffinities, which require each message to be processed by an instancewithin that pool that would otherwise fail or be inefficient outside ofthat pool. The sticky pool-aware Kafka partition assignor is designed tominimize churn while allowing an application to reserve a partition inorder to avoid any impact while scaling up. The sticky pool-aware Kafkapartition assignor may also cause partitions to stick to respectivepools so that affinities to each pool are unaffected during rebalancing.

The Kafka usage may also provide for handling affinities at the edge ofthe cloud where only one instance can process a particular message butKafka has only crude routing capabilities. In this aspect, anapplication instance with an affinity, such as, for example, aweb-socket to a specific client, supplies the client with asubscriptionld that happens to also be a Kafka routing key thatguarantees that all messages sent to that client from back end servicesarrive, within a single hop, at the correct application instance. Theapplication had previously reserved a partition, calculated as at leastone universally unique identifier (UUID) that routes to the partition,so that the UUID(s) can be offered on demand to clients as subscriptionIDs.

The Kafka usage may also provide for multi-threading of the consumptionof messages per Kafka partition while maintaining strict messageordering. In this aspect, for the vast majority of application, orderingonly has meaning for messages produced with the same routing-key. Thus,the Kafka usage may be designed to process all messages received from apartition in parallel except for those messages with the same key whichmust be processed sequentially.

In still another exemplary embodiment, resiliency patterns and a clientdiscovery service designed to overcome global load balancer (GLB)latencies is provided. Browsers and client desktops cache domain namesystem (DNS) resolution of uniform resource locators (URLs), and whenthe backend services or pools experience failures, the clients continueto attempt to generate requests to the same defunct destination. In suchdeployments, where no performant IP sprayers or gateways exist and wheremillisecond latency SLAs exit, there may be a disruption in thecontinuous availability of services. In this aspect, a client sideresiliency that complements the multi-pool, multi-instance, andmulti-data center availability for instant seamless connection isprovided. The client first discovers services and capabilities,including backup pool URLs, according to current availability and userauthorization. The discovery service provides intelligent backup URLsfor stateful services, stateless services, and external server systems.A client software development kit abstracts the resiliency, rehydration,and reconnection logic, begins network recovery, and then does aseamless login. The client user interface automatically recovers fromthe loss of a websocket or failure of a cloud microservice in a pool.

In yet another exemplary embodiment, resiliency patterns and seamlessresiliency of stateful, low latency telephony clients across multipledata centers (DCs). In each data center, stateful edge services monitoreach extension (i.e., directory number) simultaneously from differentinstances on both pools, thereby providing both instance and poolresiliency. Such services may use a de-duper that receives events fromboth pools but propagates only one pool. For phone resiliency, extension(directory number) may move from one data center to another, and theservicing fabric in both data centers may detect the move and directrequests to the new data center. Failure to login causes aresynchronization of the phone state in both data centers, thusself-healing in case discovery becomes out of synchronization.

The following table provides a list of features and specific aspectsthereof:

Stateful Stateful→Stateless Bidirectional Dealing with Vendor EgressFollow the Phone - DR Domain WebSocket High Affinity connectionsfailover Low Latency Minimize Latencies through Select Blazing Highlyconcurrent connections: Custom Sticky Kafka colocation fact Technologiesvendor systems & clients Partition Assignor Stack HA Provide HighAvailability Leverage nascent Event Starters encapsulate Standby DataCenter (DC) (HA) of CaaS, Kafka clusters resiliency in stack HighAvailability (HA) Promotion under the cover Load Circuit BreakerPatterns: Connection to Global Phone and queue monitoring Dataextractions load Balancing for end-user client and Load Balances (GLBs)load balanced across a DC balanced across Data server-to-server(API2API) for non-cloud servers Centers (DCs) invocations, with backupAvailability Zones Black Client Side Recovery Kafka moves all loadSubscriptions replicated SDK connects to other Availability (Web Socketdisconnect, to other Availability across Availability Zones AvailabilityZone Zone Failure Availability Zone failure, Zone in less than 3 sec appfailure) Grey AZ aware Sticky Partition Multiple layers of OAUTH2Authorization Cloud Config Server has all Availability Assignor isolatesnetwork defense for grey across multiple Availability the bootstrapinfo, Prod: Zone Failure issues in Availability Zones failures Zoneenvironment Bitbucket

In still another exemplary embodiment, defense mechanisms for handlinggrey failures in the cloud are provided. A first defense mechanism is asticky partitioner that is designed to handle a scenario in which onepool is bad, and even while sharing the same Kafka and Cassandra acrosstwo pools, events would zigzag across applications in the two pool,thereby increasing the probability of a grey failure when anymicroservice in a second pool begins to go bad, and also affecting alltraffic. The sticky partitioner addresses this scenario by isolatingnetwork issues in pools by primarily routing the events to the samepool, thereby ensuring that 50% of the traffic is not affected by anunhealthy grey pool.

A second defense mechanism is the use of multiple levels of defense forgrey failures so that a single failure does not equate to a requestfailure as it is retried across other pools and/or other mechanisms. Forexample, for a scenario in which an external server application issues arequest to a pool that is only partially able to service the request,thereby resulting in a failure, this defense mechanism is designed topropagate all information available for servicing the request in asecond attempt on another pool. If the second pool is able to find theremaining missing data from the first pool, then the second poolprocesses the request.

A third defense mechanism is the use of multiple layers of defense forgrey failures for stateful applications so that a single failure doesnot equate to a request failure as there are multiple resiliency designsat each stage of the microservice in order to ensure servicing therequest. For example, for a scenario in which a ribbon login failsbecause a CTI extension monitoring had failed or was interrupted, orbecause the request was routed to the wrong pool, or because thedirectory number is not in service, this defense mechanism is designedto perform several functions, including the following: CTI monitorsdirectory number changes at all times; directory number in-service andout-of-service events are propagated across both data centers; if thelogin attempt comes to a data center where the directory number is outof service, CTI will ask the other data center's CTI to publish if thedirectory number is in service in that data center; repeat a set up fromscratch for failed connections for some CTI directory number; delegatesome failed connections for some CTI directory number from one CTI to abackup CTI; and recovery code in ribbon client to go into retry mode anddetermine when the directory number status changes, therebyself-healing.

In yet another exemplary embodiment, high efficiency reliablebidirectional messaging for low latency applications is provided. Thisembodiment includes several features. A first feature is an ability tosend a Kafka event direct to the instance hosting the web-socket for thefinal leg of delivery with a minimum possible latency. This is achievedby calculating a UUID that maps to a partition owned by thenotification-service instance so that all messages sent using that UUIDas a Kafka routing key are delivered directly to the correct one of manynotification-service instances.

A second feature is an ability to scale up a number of instances withoutany latency nor disruption to existing web-socket users. This isachieved by using a custom stick partition assignor whereby the consumeris guaranteed that one partition is never removed. This also avoidstwo-hop routing.

A third feature is load balancing of system-wide events to anotherecosystem through stateless, load balanced, randomized delivery on anyof the web-sockets (WS). This feature provides an ability toload-balance events that can be consumed by a group of web-socketclients. This is achieved by allowing each member of a load-balancing(LB) group to subscribe with the name of the LB group so that futuremessages received by a notification service on a UUID that belongs tothe group can be delivered to any member.

A fourth feature allows for more than one web-socket to be part of ahigh availability (HA) group to ensure low latency and guaranteeddelivery on a surviving web-socket. This feature provides an ability tosupport clients that require a highly available pair of web-socketswhere ordered events are delivered via an “active web-socket” only, andwhen it fails, the surviving web-socket is immediately promoted to beingactive. Thus, a latency that would have occurred without the HA group iscompletely avoided. Meanwhile, the client will initiate a new backupweb-socket. To protect against failure or down-scaling, upon receiving anew web-socket request with an HA group identification, thecorresponding notification service will reject a request to create asecond web-socket in the same HA group on the same instance.

A fifth feature provides an ability to support message delivery fromclients in multiple pools. This is achieved by using Kafka's nativeability to route messages using a routing key so that the producer ofthe message only needs to know the Kafka cluster address.

A sixth feature provides an ability to subscribe anywhere, replicateeverywhere, and notify anywhere. This feature further provides anability to support message delivery from clients in multiple datacenters (DCs) whereby when a message is received in one DC where theUUID is not recognized, the notification service will query a databaseto determine the Kafka cluster associated with the UUID so that themessage is delivered in a second hop. In this manner, the client neednot be concerned with the DC affinity of the web-socket.

A seventh feature provides an ability to act as a durable messageprovider by which no messages are lost. This feature further provides anability to cache events in case a client is temporarily absent,providing a fire and forget service for microservices. This is achievedby caching undeliverable events for a configurable amount of time aftera web-socket disconnects. On reconnection, the client will present, viaa web-socket message, an identifier that maps it to the previously usedUUID, and the notification service will then deliver all cached messagesbefore continuing with normal message delivery.

An eighth feature provides a client side home pool, which allows clientsto receive events more quickly by directing them to a more efficientpool. The efficiency is improved through locality, speedier delivery ofevents for co-located microservices, and Kafka, together with vendorgear for a particular user.

A ninth feature provides a common utility framework to notify any clientindependent of any type of microservices (i.e., a sender of an event).The common utility framework manages the client notification channel andis a common utility for services, thus abstracting them from thedelivery details.

A tenth feature provides client session management via terminationlifecycle events, which are being sent to all microservices. An eleventhfeature provides abstracting of the Kafka resiliency architecture (e.g.,dual DC or standby DC) via a mere web-socket delivery.

Taken together, these features provide additional advantages, includingthe following: First, ribbon clients were preferred not to talk to Kafkabecause it would require a partition for each user, but an excessivenumber of partitions would not be supported by Kafka, because of a lackof scalability, or else users would receive events that were intendedfor other users. Second, web-sockets are used for low latency, but thepresent embodiment uses a common web-socket towards a client, and routesall events from various microservices on the same channel.

There are many scenarios where a client sends requests to a single IPAddress repeatedly even though the services are down. This could be dueto local DNS resolution caching, and could also be due to delays causedby the time taken for GLBs to detect the services being down.

The latencies in the above-described scenario disrupt telephonycommunications due to the nature of real time low latency communication.Despite providing resiliency for multipool/multi-data centermicroservices, clients send requests to the services that are down, dueto local DNS resolution caches, for 20 minutes or more, depending on theoperating system and browser settings.

High Efficiency, Reliable Bidirectional Messaging for Low LatencyApplications: Applies to 1) systems that use a message bus based ontopics and partitions for very high throughput; 2) many single instanceapplications that operate independently; and 3) many multi-instanceapplications that require load-balancing.

In an exemplary embodiment, the present disclosure provides methodsfor: 1) latency-free scale-up and routing messages directly to aspecific target application instance using a messaging system that usestopics, routing keys and partitions; 2) reliably delivering messages tothe application despite failures in the client or of a networkconnection; 3) load-balancing messages across multiple instances of anapplication that form an application-type grouping; 4) supporting theabove in multiple Availability Zones and Data Centers; and 5) handlingoverload by dropping the lowest priority messages.

In conventional systems, clients that wish to subscribe directly to atopic message system may use a dedicated topic based on theclient-identifier. The message producers produce messages for specificclients to the client-specific topic based on the client-identifier. Theclient subscribes for messages using a topic name derived from theclient's identifier. Alternatively, clients that wish to subscribedirectly to a topic message system may use a shared topic with eachpartition dedicated to at most one client based on theclient-identifier. The client and message producer(s) are coupled usingan external client-identifier to partition mapping database. The clientuses manual partition assignment to allocate their dedicated partitionto themselves. However, both of these approaches are typically scalableto only a few thousand clients because of the overhead of having so manytopic-partitions for the brokers to manage.

Clients that wish to subscribe to a microservice that delivers eventsvia a WebSocket must incur latency as the service performs multiple-hoprouting to deliver the event to the correct instance. Anotheralternative would be to use broadcast messages but this reducesscalability of the solution.

Another conventional approach is for each instance of NotificationService to subscribe for all events and to discard those events thatcannot be routed to a client. However, this approach is inefficient, isnot scalable to hundreds of thousands of events per second, and does notprovide reliable delivery in the case of temporarily unavailablewebsockets.

Another conventional approach is for a client to poll a database todetect when a message has to be sent to the client. Backend servicesthat wish to send a message to the client, deposit the message in thedatabase so that it will be picked up by the polling thread. However,this approach introduces unnecessary latency and its scalability islimited by the need to poll for a large number of clients. Further, yetanother conventional approach is to use a “sticky sessions” on afront-end HTTP load-balancer.

In an exemplary embodiment, the following is a glossary of terms to beused below:

Notification Service: A microservice hosting websockets for exchangingevents with many clients. Receives subscription messages from client andmaintains a map of ND to websocket to facilitate delivery of events.This is a common utility used by many other microservices in order todeliver the message to the client. The actual message content is opaqueto the notification service.

Client is the user application that wants to receive events. It obtainsa unique ID from Notification Service and then uses this ID in allsubscriptions to event generating microservices (‘Event Provider’).

Event Provider microservice: These microservices are responsible forgenerating events of a certain functionality (e.g. Call or Presence orUser-Status). Receives a subscription from the client and then createsmessages suitable for sending to a client in JSON format and then sendsthese messages to the Notification Service for delivery to the specificclient in accordance with the client's subscription.

FIG. 9 is a flowchart 900 of a method for routing a message to anapplication in a messaging platform environment, according to anexemplary embodiment.

Method-1: Single-hop routing to service hosting websockets: In a systemwhere a Kafka message can only be processed by one of many consumers,one conventional approach is to accept that messages with a routing keywill usually arrive at the wrong instance and correct that using two hoprouting together with a cache of “key-to-instance” and“instance-to-partition” mappings. Another conventional approach is forthe message Producer to co-operate with the Consumer by producing themessage to a particular partition that it knows is owned by the targetConsumer instance. This, however, couples Producer and Consumer andrequires communication to handle setup and rebalancing. Use of Kafka isdiscouraged where this requirement exists.

Referring to FIG. 9, in an exemplary embodiment, the present disclosureprovides a mechanism to solve the problem in the Consumer whilemaintaining loose or no coupling between Producer and Consumer, asfollows: 1) On startup, the Kafka Consumer registers with a stickypartitions assignor and acquires 1:n partitions (operation S902. 2)Consumer identifies one of the n partitions, e.g., the lowest partition,to be its sticky partition (operation S904). 3) Consumer generates astore of routing keys that it knows route to the sticky partition(operation S906) by creating random keys and either 3a) applies Kafka'shash+mod algorithm and discards those keys which do not map to thesticky partition, or 3b) produces them to the “inbound” topic and onconsumption, stores keys from the sticky partition. 4) Consumers receivea subscription for a service supplied by the consumer via any mechanism(REST, Kafka, etc.) (operation S908). It returns an unused routing-keyfrom its store as a subscription-identifier. 5) The client, on receivinga subscription response with a subscription-identifier, subscribes toother services using the same identifier (operation S910). 6) When theother services wish to send a message to their client, they send eachKafka message using the client's identifier as the routing key. Themessage will now route directly to the one-and-only consumer capable ofprocessing that message (operation S912).

FIG. 8 is a data flow diagram 800 that illustrates consumer affinity,according to an exemplary embodiment. Referring to FIG. 8, the Consumerhas no control over which UI's connect to it via a websocket. The resultis that a message from Producer Sa-1 destined to only one of the manyUI's must be routed to the particular instance N-3 that hosts thewebsocket. This must be done without the Producer having any knowledgeof which partitions are assigned to the Consumer and without anyknowledge of websocket wiring, and to reduce latency, should be achievedin a single hop.

In one exemplary embodiment, an assignor of step-1 is Kafka's standardsticky partition assignor, which reduces the probability that thepartition is moved during rebalancing. In the case where the partitionis removed due to rebalancing, two hop routing is required together witha cache of “key-to-instance” and “instance-to-partition” mappings.

In another exemplary embodiment, a customized Kafka partition assignoralgorithm is used to guarantee that in the event of rebalancing (i.e.,where the number of consumers increases or decreases), the stickypartition is never removed from the consumer that initially acquired it,for as long as that consumer remains healthy. 1) On Kafka rebalancing,when a consumer-instance has acquired its first set of partitions, itchooses one as its “hard sticky partition.” 2) On every subsequentrebalance, 2a) the consumer is queried for metadata that will besupplied to the lead assignor and returns either only the hard-stickypartition or all existing partitions with a weighting for eachpartition, the hard-sticky being the most sticky; 2b) on receipt of theset of metadata from all instances of the consumer-group, the leadassignor reads the hard-sticky partition from every instance andallocates it back to its owner. It then allocates the remainingpartitions using the supplied weightings if any or using any otheralgorithm such as “sticky” or “round-robin”; 2c) the lead assignorreturns the assignment decisions which are distributed to consumersusing the existing mechanism; and 2d) consumers receive their newassignment which includes the hard-sticky partition.

Scaling-up Notification Service: In an exemplary embodiment, thisapproach supports scaling up notification service without any impact tothe client. In the exemplary embodiment described above, only one of theKafka partitions was used to receive messages. Remaining partitions areavailable for assignment to new instances and will only be used ifselected as the primary sticky partition on the new instance. Scalingdown of notification service does cause websockets to break.

Management of Notification Identifier (NID) Lifecycle: In an exemplaryembodiment, the following approach does not require the client togracefully unsubscribe when no longer using the websocket.

Setup: Topic “notification_life_cycle” with produce permissions grantedto notification-service and client permissions granted to all clientmicroservices. Client microservices consume from this topic using anAvailability Zones-specific consumer-id with the effect that each AZgets on copy of each message.

1) Client creates a websocket. 2) Notification Service returns a NID. 3)Client subscribes to event source microservices using the NID as itssubscription ID. 4) Event source microserivces send events that matchthe subscription to the client via the notification service. 5)Websocket drops for any reason. 6) Notification Service detects that thewebsocket drops and starts timer A. Note: if the instance hosting thewebsocket dropped, then timer A is started by the first microservicethat fails to deliver an event. 7) If the client reconnects at a newinstance using the old NID. then the NID-to-instance mapping is updatedin the cache. 8) On expiry of timer A, read the NID-to-instance mapping.If the mapping still returns the local instance and if the localinstance does not have a websocket corresponding to the NID, send aLifecycleChanged {state=terminated} message to topic“notification_life_cycle.” 9) On receiving a “notification_life_cycle”event, delete the subscription.

Refresh: For a new websocket, Notification Service starts Timer B.

FIG. 10 is a flowchart 1000 of a method for load-balancing a delivery ofmessages in a messaging platform environment, according to an exemplaryembodiment.

Method-2: Load-balance delivery of messages: In addition to single userclient applications, there are clusters of server applications that alsowould like to receive events with high reliability, low latency as wellas with load-balanced distribution across each instance in the servercluster. The notification microservice also caters to such serverapplications and provides them a load-balanced, highly available, lowlatency set of events using a concept of load-balanced and highavailability grouping of websockets. All members of the same group areeligible for selection in order to deliver a message. Each clientinstance below refers to an instance of the server application thatwishes to receive the events.

Referring to FIG. 10: 1) Each client instance establishes a websocketconnection and sends a JSON subscribe with a “LB-group” attribute with avalue that uniquely identifies the client grouping. 2) Notificationservice obtains a UUID subscription ID as per Method-1 for thesubscription (operation S1002). 3) Notification service caches themapping of the “LB-group” value to a list of IDs for the given LB-group(operation S1004) and returns the ID in a JSON subscribe response(operation S1006). 4) Client subscribes to “Event Provider”microservices using the ID obtained from step 3 and “LB-group” value. 5)Each “Event Provider” service receiving a subscription in step 4 cachesthe subscription and adds it to a randomized list of IDs for the given“LB-group” value.

6) On receiving an event, each “Event Provider” uses its cache to get acopy of the list of matching subscriptions. Non-group subscriptions arehandled as per Method-1. If the list contains LB-group subscription(s),one subscription is selected at random from the LB-group list and thenotification event is propagated using the ID of that subscription asthe routing key. The other “LB-group” subscriptions are added at randomto an “alternate-ID” header on the same message for resiliency reasons.7) On receiving this notification event (operation S1008), thenotification service will attempt to deliver to the client whosewebsocket subscription ID matches the ID specified in the routing key(operation S1010). 7a) On failure to deliver, it attempts to deliver tothe next ID in the LB-group list that also has a websocket on the samenotification-service instance (operation S1012). 7b) On failure todeliver in step 7a, it removes the ID on the local instance from theheader and repeats so that all IDs on the local instance have beenattempted. 7c) On failure to deliver in step 7b, it sends to the nextNID in the list using a second hop.

FIG. 11 is a flowchart 1100 of a method for ensuring a delivery of amessage in a messaging platform environment despite a network connectionfailure, according to an exemplary embodiment.

Method-3: Reliably deliver messages despite failures of a networkconnection: In an exemplary embodiment, the client will establish one ormore redundant websocket connections to the notification service.Notification Service effectively uses one of the websockets as theprimary and only on failure switches to a backup. The client mustreceive all messages via one of its websockets so that ordering ismaintained. If a client unexpectedly loses a websocket connection, thenit may create a new connection with the same high-availability (HA)“HA-group.”

Referring to FIG. 11: 1) Client establishes a websocket connection andsends a JSON subscribe with an “HA-group” attribute with a value that isunique to the system. 2) Notification service determines if it alreadyhosts a connection to the same HA-group at this instance, and if yes,for anti-affinity reasons in case the notification service instancefails, rejects the subscription request and closes the websocket withappropriate code (e.g. SERVICE_OVERLOAD). 3) Notification serviceobtains a UUID subscription ID as per Method-1 for the subscription(operation S1102). 4) Notification service caches the mapping of the“HA-group” value in an ordered list of IDs (operation S1104) and returnsthe ID in a JSON subscribe response (operation S1106). 5) Client repeatsstep 1 for the desired number of redundant connections.

6) Client subscribes to other microservices using the ID obtained instep 4. 7) Client service, having received a subscription from step 6,caches the subscription and adds it to a list of IDs for the given“HA-group” value. 8) On receiving an event, each ‘Event Provider’service uses its cache to get a list of matching subscriptions.Subscriptions with the same HA-group are removed from the list. Theremaining subscriptions are handled as per Method-1. The firstsubscription is selected from the HA-group list and the notificationevent is propagated using the ID of that subscription as the routingkey. The other members of the list are added, in order, to an“alternate-ID” header on the same message. 9) On receiving thisnotification event (operation S1108), the notification service willattempt to deliver the message to the ID specified in the routing key(operation S1110). 9a) On failure to deliver, it attempts to deliver tothe next ID in the “alternate-ID” header that is on the local instance(there should be none). 9b) On failure to deliver in step 9a, it removesthe local ID from “alternate-ID” header and resends the message usingthe next NID from the remaining alternate-IDs (operation S1112). 9c) Onfailure to deliver in step 9b, undeliverable messages are dropped.

In a variant exemplary embodiment, messages that cannot be delivered in9c may be cached for later delivery: 1) Client loses its websocket andreconnects using the ID from the previous session. 2) NotificationService validates that it still has a cached record of the old ID,returns the subscription response containing the old ID, and thendelivers all messages from its cache before allowing any new messages tobe delivered.

In another variant exemplary embodiment, two hop routing introduced inthe previous exemplary embodiment is avoided: 1) Client loses itswebsocket and reconnects using the ID from the previous session. 2)Notification Service validates that it still has a cached record of theold ID, returns the subscription response containing a new ID, and thendelivers all messages from its cache before allowing any new messages tobe delivered. 3) On receiving a new ID, client must resubscribe to allservices that it has subscribed using the old ID.

Method-4: Support multiple Availability Zones and Data Centers: 1)Client establishes a websocket connection and subscribes as per Method1, 2 or 3 as described above. 2) Notification service caches thesubscription in a distributed database, replicated across all DCs,before returning the ID in the subscription response. The cachedsubscription contains the data-center-id of the websocket. 3) Clientsubscribes to any client-microservice as per Method 1, 2 or 3 asdescribed above. 4) Event Provider service, on receiving an event,queries its distributed cache to get a list of matching subscriptions.Subscriptions are sorted into sub-lists per data-center-id, and routinginformation is obtained for each data-center-id (e.g. Kafka cluster andtopic) and then propagated to the notification-service in each DC.

In a variant exemplary embodiment, step 4 above is replaced by thefollowing: 1) Event Provider service, on receiving an event, sendsevents directly to its local Notification Service as per Method-1 asdescribed above. 2) Notification Service, on receiving an event that isnot deliverable in that DC, queries its distributed cache to get asubscription for the given routing key. On finding a subscription with anon local-DC ID, Notification service maps the subscription's DC-ID to aKafka cluster and topic and sends it to the remote DC. To prevent aninfinite loop, it may include a “remaining-hops=0” header so that themessage will not be sent back to a DC that has already processed it.

Method-5: Overload protection: 1) Event-Provider service adds header“executionTimeoutMs” to all messages that can be dropped in an overloadcondition. The value of the header increases with priority of themessage. 2) Notification service consumes a message and starts anexecution timer. 3) Notification service attempts to submit a task to afinite-sized work queue for ordered processing. The work-queue may be asequential-executor. If the work queue is currently full, the submissionwill be delayed. The maximum time allowed on the submit API iscalculated as the amount of time remaining. 4) When the task is removedfrom the work-queue in preparation for execution, only allow executionto proceed if the amount of time remaining is greater than zero.

In a variant exemplary embodiment, in addition to the above: 1) ClientService adds header “producedTime” to all messages that can be droppedin an overload condition. The value of the header is normally in Zulutime. 2) Notification service consumes a message and starts an executiontimer. 3) Notification service attempts to submit a task to afinite-sized work queue for ordered processing. The work-queue may be asequential-executor. If the work queue is currently full, the submissionwill be delayed. The maximum time allowed on the submit API iscalculated as currentTime+executionTimeoutMs−producedTime. 4) When thetask is removed from the work-queue in preparation for execution, onlyallow execution to proceed if the amount of time remaining is greaterthan zero.

Accordingly, with this technology, an optimized process for handlinglarge number of customer service interactions to ensure efficient andaccurate interaction servicing results is provided.

Although the invention has been described with reference to severalexemplary embodiments, it is understood that the words that have beenused are words of description and illustration, rather than words oflimitation. Changes may be made within the purview of the appendedclaims, as presently stated and as amended, without departing from thescope and spirit of the present disclosure in its aspects. Although theinvention has been described with reference to particular means,materials and embodiments, the invention is not intended to be limitedto the particulars disclosed; rather the invention extends to allfunctionally equivalent structures, methods, and uses such as are withinthe scope of the appended claims.

For example, while the computer-readable medium may be described as asingle medium, the term “computer-readable medium” includes a singlemedium or multiple media, such as a centralized or distributed database,and/or associated caches and servers that store one or more sets ofinstructions. The term “computer-readable medium” shall also include anymedium that is capable of storing, encoding or carrying a set ofinstructions for execution by a processor or that cause a computersystem to perform any one or more of the embodiments disclosed herein.

The computer-readable medium may comprise a non-transitorycomputer-readable medium or media and/or comprise a transitorycomputer-readable medium or media. In a particular non-limiting,exemplary embodiment, the computer-readable medium can include asolid-state memory such as a memory card or other package that housesone or more non-volatile read-only memories. Further, thecomputer-readable medium can be a random-access memory or other volatilere-writable memory. Additionally, the computer-readable medium caninclude a magneto-optical or optical medium, such as a disk or tapes orother storage device to capture carrier wave signals such as a signalcommunicated over a transmission medium. Accordingly, the disclosure isconsidered to include any computer-readable medium or other equivalentsand successor media, in which data or instructions may be stored.

Although the present application describes specific embodiments whichmay be implemented as computer programs or code segments incomputer-readable media, it is to be understood that dedicated hardwareimplementations, such as application specific integrated circuits,programmable logic arrays and other hardware devices, can be constructedto implement one or more of the embodiments described herein.Applications that may include the various embodiments set forth hereinmay broadly include a variety of electronic and computer systems.Accordingly, the present application may encompass software, firmware,and hardware implementations, or combinations thereof. Nothing in thepresent application should be interpreted as being implemented orimplementable solely with software and not hardware.

Although the present specification describes components and functionsthat may be implemented in particular embodiments with reference toparticular standards and protocols, the disclosure is not limited tosuch standards and protocols. Such standards are periodically supersededby faster or more efficient equivalents having essentially the samefunctions. Accordingly, replacement standards and protocols having thesame or similar functions are considered equivalents thereof.

The illustrations of the embodiments described herein are intended toprovide a general understanding of the various embodiments. Theillustrations are not intended to serve as a complete description of allthe elements and features of apparatus and systems that utilize thestructures or methods described herein. Many other embodiments may beapparent to those of skill in the art upon reviewing the disclosure.Other embodiments may be utilized and derived from the disclosure, suchthat structural and logical substitutions and changes may be madewithout departing from the scope of the disclosure. Additionally, theillustrations are merely representational and may not be drawn to scale.Certain proportions within the illustrations may be exaggerated, whileother proportions may be minimized. Accordingly, the disclosure and thefigures are to be regarded as illustrative rather than restrictive.

One or more embodiments of the disclosure may be referred to herein,individually and/or collectively, by the term “invention” merely forconvenience and without intending to voluntarily limit the scope of thisapplication to any particular invention or inventive concept. Moreover,although specific embodiments have been illustrated and describedherein, it should be appreciated that any subsequent arrangementdesigned to achieve the same or similar purpose may be substituted forthe specific embodiments shown. This disclosure is intended to cover anyand all subsequent adaptations or variations of various embodiments.Combinations of the above embodiments, and other embodiments notspecifically described herein, will be apparent to those of skill in theart upon reviewing the description.

The Abstract of the Disclosure is submitted with the understanding thatit will not be used to interpret or limit the scope or meaning of theclaims. In addition, in the foregoing Detailed Description, variousfeatures may be grouped together or described in a single embodiment forthe purpose of streamlining the disclosure. This disclosure is not to beinterpreted as reflecting an intention that the claimed embodimentsrequire more features than are expressly recited in each claim. Rather,as the following claims reflect, inventive subject matter may bedirected to less than all of the features of any of the disclosedembodiments. Thus, the following claims are incorporated into theDetailed Description, with each claim standing on its own as definingseparately claimed subject matter.

The above disclosed subject matter is to be considered illustrative, andnot restrictive, and the appended claims are intended to cover all suchmodifications, enhancements, and other embodiments which fall within thetrue spirit and scope of the present disclosure. Thus, to the maximumextent allowed by law, the scope of the present disclosure is to bedetermined by the broadest permissible interpretation of the followingclaims, and their equivalents, and shall not be restricted or limited bythe foregoing detailed description.

What is claimed is:
 1. A method for load-balancing a delivery ofmessages over a plurality of connection oriented sessions from aplurality of applications, the method being implemented by at least oneprocessor in a Kafka messaging platform environment, the methodcomprising: obtaining, by the at least one processor, a firstsubscription from a first application containing a first load balancinggroup identification; assigning, by the at least one processor, a firstsubscription identification to the first subscription; caching, by theat least one processor, a mapping of the first load balancing groupidentification to a list of subscription identifications and a mappingof the first subscription identification to a connection orientedsession; transmitting, to the first application by the at least oneprocessor, a subscribe response that includes the first subscriptionidentification; receiving, by the at least one processor, a notificationevent that includes the first subscription identification; andattempting, by the at least one processor, to deliver a message to thefirst application when the cached first subscription identification mapsto a connection oriented session of the first application.
 2. The methodof claim 1, wherein the notification event is received from an eventprovider that has received the notification event and randomly selectedthe first subscription identification from the list of subscriptionidentifications.
 3. The method of claim 1, further comprising: when theattempting to deliver the message fails when using a first connectionoriented session that corresponds to the first subscriptionidentification, using the list of subscription identifications toidentify a second connection oriented session that relates to a secondapplication for which a corresponding subscription identification has amatching load balancing group identification as the first connectionoriented session; and attempting to deliver the message to the secondapplication.
 4. The method of claim 1, further comprising: evaluating,by the at least one processor, a total number of subscriptionidentifications for a first availability zone from among a plurality ofavailability zones and for the first load balancing group identificationfrom among a plurality of load balancing group identifications; andtriggering, by the at least one processor, a redistribution ofconnection oriented sessions with the first application.
 5. A computingapparatus for load-balancing a delivery of messages over a plurality ofconnection oriented sessions from a plurality of applications in a Kafkamessaging platform environment, the computing apparatus comprising: aprocessor; a memory; and a communication interface coupled to each ofthe processor and the memory, wherein the processor is configured to:obtain a first subscription from a first application containing a firstload balancing group identification; assign a first subscriptionidentification to the first subscription; cache a mapping of the firstload balancing group identification to a list of subscriptionidentifications and a mapping of the first subscription identificationto a connection oriented session; transmit, to the first application viathe communication interface, a subscribe response that includes thefirst subscription identification; receive, via the communicationinterface, a notification event that includes the first subscriptionidentification; and attempt to deliver a message to the firstapplication when the cached first subscription identification maps to aconnection oriented session of the first application.
 6. The computingapparatus of claim 5, wherein the notification event is received from anevent provider that has received the notification event and randomlyselected the first subscription identification from the list ofsubscription identifications.
 7. The computing apparatus of claim 5,wherein the processor is further configured to: when the attempt todeliver the message fails when using a first connection oriented sessionthat corresponds to the first subscription identification, use the listof subscription identifications to identify a second connection orientedsession that relates to a second application for which a correspondingsubscription identification has a matching load balancing groupidentification as the first connection oriented session; and attempt todeliver the message to the second application.
 8. The computingapparatus of claim 5, wherein the processor is further configured to:evaluate a total number of subscription identifications for a firstavailability zone from among a plurality of availability zones and forthe first load balancing group identification from among a plurality ofload balancing group identifications; and trigger a redistribution ofconnection oriented sessions with the first application.
 9. A method forensuring a delivery of a message in a Kafka messaging platformenvironment despite a network connection failure, the method beingimplemented by at least one processor, the method comprising: obtaining,by the at least one processor from a first application, a firstsubscription containing a first high availability group identification;assigning, by the at least one processor, a first subscriptionidentification to the first subscription; caching, by the at least oneprocessor, a mapping of the first high availability group identificationto an ordered list of subscription identifications; transmitting, to thefirst application by the at least one processor, a subscribe responsethat includes the first subscription identification; receiving, by theat least one processor, a notification event that includes the firstsubscription identification; and attempting, by the at least oneprocessor, to deliver a message to the first application when the firstsubscription identification matches a first connection oriented sessionsubscription of the first application.
 10. The method of claim 9,wherein the notification event is received from an event provider thatselected the first subscription identification from the ordered list ofsubscription identifications based on the first subscriptionidentification being listed first in an order of the ordered list. 11.The method of claim 9, further comprising: when the attempting todeliver the message fails, determining, from the ordered list ofsubscription identifications, at least one subscription identificationfor which a high availability group identification matches the firsthigh availability group identification of the first subscription, andidentifying a second subscription identification that matches a secondconnection oriented session of the first application; and attempting todeliver the message to the first application using the second connectionoriented session.